snowflake.snowpark.Table.delete¶
- Table.delete(condition: Column | None = None, source: DataFrame | None = None, *, statement_params: Dict[str, str] | None = None, block: bool = True) DeleteResult [source]¶
- Table.delete(condition: Column | None = None, source: DataFrame | None = None, *, statement_params: Dict[str, str] | None = None, block: bool = False) snowflake.snowpark.AsyncJob
Deletes rows in a Table and returns a
DeleteResult
, representing the number of rows deleted.- Parameters:
condition – An optional
Column
object representing the specified condition. It must be provided ifsource
is provided.source – An optional
DataFrame
that is included incondition
. It can also be anotherTable
.statement_params – Dictionary of statement level parameters to be set while executing this action.
block – A bool value indicating whether this function will wait until the result is available. When it is
False
, this function executes the underlying queries of the dataframe asynchronously and returns anAsyncJob
.
Examples:
>>> target_df = session.create_dataframe([(1, 1),(1, 2),(2, 1),(2, 2),(3, 1),(3, 2)], schema=["a", "b"]) >>> target_df.write.save_as_table("my_table", mode="overwrite", table_type="temporary") >>> t = session.table("my_table") >>> # delete all rows in a table >>> t.delete() DeleteResult(rows_deleted=6) >>> t.collect() [] >>> # delete all rows where column "a" has value 1 >>> target_df.write.save_as_table("my_table", mode="overwrite", table_type="temporary") >>> t.delete(t["a"] == 1) DeleteResult(rows_deleted=2) >>> t.collect() [Row(A=2, B=1), Row(A=2, B=2), Row(A=3, B=1), Row(A=3, B=2)] >>> # delete all rows in this table where column "a" in this >>> # table is equal to column "a" in another dataframe >>> target_df.write.save_as_table("my_table", mode="overwrite", table_type="temporary") >>> source_df = session.create_dataframe([2, 3, 4, 5], schema=["a"]) >>> t.delete(t["a"] == source_df.a, source_df) DeleteResult(rows_deleted=4) >>> t.collect() [Row(A=1, B=1), Row(A=1, B=2)]